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A self-organizing map framework for detection of man-made structures and changes in satellite imagery

Proceedings article published in 2006 by Matthieu Molinier ORCID, Jorma Laaksonen, Tuomas Häme
This paper is available in a repository.
This paper is available in a repository.

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Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
Question mark in circle
Published version: policy unknown

Abstract

2006 IEEE International Geoscience and Remote Sensing Symposium. IGARSS. Denver, CO, USA, 31 July - 4 August, 53 - 56 ; Content-based querying allows efficient retrieval of images based on the information they contain, rather than acquisition date or geographical extent. We extend the potential of a content-based image retrieval (CBIR) system based on Self- Organizing Maps (SOMs), to the analysis of remote sensing data. A database was artificially created by splitting each satellite image to be analyzed into small images. After training the CBIR system on this imagelet database, both interactive and off-line queries were made to detect man-made structures, as well as changes. Experimental results suggest that this new approach is suitable for analyzing very high-resolution optical satellite imagery. Possible applications include interactive detection of man-made structures and supervised monitoring of sensitive sites.